SOTAVerified

Multi-class Classification

Multi-class classification is a type of supervised learning where the goal is to assign an input to one of three or more distinct classes. Unlike binary classification (which has only two classes), multi-class classification handles multiple labels and uses algorithms like logistic regression, decision trees, random forests, SVMs, or neural networks to predict the correct category based on the features of the input data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 903 papers

TitleStatusHype
Convergence of Uncertainty Sampling for Active Learning—0
Analysis of French Phonetic Idiosyncrasies for Accent RecognitionCode0
Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding—0
Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis—0
Distribution-Free Federated Learning with Conformal Predictions—0
Instance-based Label Smoothing For Better Calibrated Classification NetworksCode0
Pairwise Margin Maximization for Deep Neural NetworksCode0
Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks—0
Tribuo: Machine Learning with Provenance in JavaCode2
Emoji Prediction from Twitter Data using Deep Learning ApproachCode1
LexGLUE: A Benchmark Dataset for Legal Language Understanding in EnglishCode1
Generative Adversarial Networks based on Mixed-Attentions for Citation Intent Classification in Scientific Publications—0
Introducing the DOME Activation Functions—0
Improving the Accuracy of Learning Example Weights for Imbalance Classification—0
Exploiting Class Activation Value for Partial-Label LearningCode1
Can multi-label classification networks know what they don't know?Code1
Multi-class Probabilistic Bounds for Self-learning—0
Multi-loss ensemble deep learning for chest X-ray classification—0
Violence Detection in Videos—0
Language Models are Few-shot Multilingual LearnersCode1
Predicting Loss Risks for B2B Tendering Processes—0
OffendES: A New Corpus in Spanish for Offensive Language Research—0
On the Usefulness of Personality Traits in Opinion-oriented Tasks—0
Information-theoretic Classification Accuracy: A Criterion that Guides Data-driven Combination of Ambiguous Outcome Labels in Multi-class ClassificationCode0
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method—0
Show:102550
← PrevPage 18 of 37Next →
All datasetsCOVID-19 CXR DatasetCOVID chest X-rayReuters-52TII-SSRC-23Training and validation dataset of capsule vision 2024 challenge.

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COVID-CXNetAccuracy (%)94.2—Unverified
#ModelMetricClaimedVerifiedStatus
1COVID-ResNetF1 score0.9—Unverified
#ModelMetricClaimedVerifiedStatus
1SVM (tficf)Macro F173.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Extra TreesF1-Score93.36—Unverified
#ModelMetricClaimedVerifiedStatus
1Multi-Model EnsembleMean AUC0.99—Unverified